The SARS-CoV-2 outbreak made clear the urgent need to depart from traditional statistics, typically released with a lag and available at a relatively low frequency. This led to unparalleled efforts to put forward high-frequency indicators to track economic developments timely. By resorting to non-traditional data sources, we propose a novel daily economic indicator to track economic activity in Portugal. It corresponds to the latent variable of a set of daily series within a factor model framework. We find a sudden and sharp drop in economic activity in mid-March 2020, when the lockdown of several activities was declared due to the COVID-19 pandemic. Since in this approach we address the complexities of high-frequency data without further smoothing, we are able to identify sudden changes of economic activity in a timely and daily manner in contrast with other approaches.
Keywords: COVID-19; Daily economic index; Factor model; High-frequency; Measurement of economic activity.
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